Infusion system which utilizes one or more sensors and additional information to make an air determination regarding the infusion system

ABSTRACT

In one step of a method for infusing an infusion fluid, the infusion fluid is pumped through a fluid delivery line of an infusion system. In another step, measurements are taken with at least one sensor connected to the infusion system. In an additional step, an air determination is determined with at least one processor. The air determination is related to air in the fluid delivery line. The air determination is based on the measurements taken by the at least one sensor. The air determination is further based on: (1) medication information regarding the infusion fluid or infusion information regarding the infusion of the infusion fluid; or (2) multi-channel filtering of the measurements from the at least one sensor or non-linear mapping of the measurements from the at least one sensor; and statistical process control charts applied to the multi-channel filtered measurements or applied to the non-linear mapped measurements.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

Any and all applications for which a foreign or domestic priority claimis identified in the Application Data Sheet as filed with the presentapplication are hereby incorporated by reference under 37 CFR 1.57.

FIELD OF THE DISCLOSURE

This disclosure relates to detection systems and methods for detectingan end of bag (EOB) event or air in an infusion system.

BACKGROUND

Infusion pumps often do not have an end-of-infusion detection system.Instead, an air-in-line alarm is provided in the event that themedication container becomes prematurely empty and air is present in theinfusion line. However, many customers utilize the air-in-line alarm asa mechanism to detect when the medication container is empty rather thantitrate an unknown quantity of drug containing fluid after the setvolume to be infused (VTBI) is complete. Caregivers often struggle withdelivering 100% of the prescribed medication to a patient because thediluent typically varies in volume up to approximately 10%.

Existing strategies for detecting air often involve the use ofultrasonic sensors that are physically located on opposite sides of atubing segment. When fluid is present in the tube, propagation of theacoustic signal is efficient and produces a large electrical signal viathe receiver circuit. On the other hand, the presence of air in the tubecauses an acoustical open circuit which substantially attenuates thedetected signal. In current practice, detection of air in the tubingsegment is often performed on the basis of a simple (static) air-fluidboundary or threshold that is applied to the air sensor voltage signal.When the air sensor signal moves beyond the pre-defined air/fluidthreshold, an alarm condition occurs and the IV infusion is paused.

However, when the medication container is emptied (i.e., EOB reached)during an infusion program, a transition occurs from delivery of fluidto air. A film of liquid trails the liquid front as it moves in thetube. This film can break up leading to a stationary fluid dropletformation between the ultrasound transducers that is large enough tocreate an acoustic short circuit, yet small enough to allow air to pass.This acoustic short circuit can produce an absolute sensor signalsimilar to that of a fluid, which will cause false indication of fluidin the line and fail to detect the EOB and air in the line.

Currently, there exist methods/algorithms that utilize plunger forcesensor readings to detect the presence of air in a plunger chamber.Several pumps made by Hospira, Inc. involve the use of a cassette with achamber that is compressed by an actuated plunger to pump fluid at acontrolled rate from the drug container to the patient. The measuredforce during a pumping cycle is directly related to the type of fluid inthe chamber. For instance, fluids are relatively incompressible andgenerate a higher and different force profile than air.

However, using the existing force algorithms for detecting EOB oftenleads to a large number of false positives since the medication type(e.g., frothy fluids), proximal/distal pressure change and other factorscan cause variability in force sensor observations.

A system and method is needed to overcome one or more issues of one ormore of the current infusion systems and methods in order to detect anEOB event or to determine whether air is in the infusion system.

SUMMARY

In one embodiment, an infusion system for being operatively connected toa fluid delivery line and to an infusion container containing aninfusion fluid is disclosed. The infusion system includes a pump, atleast one sensor, at least one processor, and a memory. The at least onesensor is connected to the pump or the fluid delivery line. The at leastone sensor is configured to indicate whether air is in the fluiddelivery line. The at least one processor is in electronic communicationwith the pump and the at least one sensor. The memory is in electroniccommunication with the at least one processor. The memory includesprogramming code for execution by the at least one processor. Theprogramming code is configured to determine an air determination relatedto the air in the fluid delivery line. This determination is based onmeasurements taken by the at least one sensor. This determination isalso based on: (1) medication information regarding the infusion fluidor infusion information regarding the infusion of the infusion fluid; or(2) multichannel filtering of the measurements from the at least onesensor or non-linear mapping of the measurements from the at least onesensor; and statistical process control charts applied to themulti-channel filtered measurements or applied to the non-linear mappedmeasurements.

In another embodiment, a method for infusing an infusion fluid isdisclosed. In one step, infusion fluid is pumped through a fluiddelivery line of an infusion system. In another step, measurements aretaken with at least one sensor connected to the infusion system. In anadditional step, an air determination is determined with at least oneprocessor. The air determination is related to air in the fluid deliveryline. The air determination is based on the measurements taken by the atleast one sensor. The air determination is further based on: (1)medication information regarding the infusion fluid or infusioninformation regarding the infusion of the infusion fluid; or (2)multi-channel filtering of the measurements from the at least one sensoror nonlinear mapping of the measurements from the at least one sensor;and statistical process control charts applied to the multi-channelfiltered measurements or applied to the non-linear mapped measurements.

The scope of the present disclosure is defined solely by the appendedclaims and is not affected by the statements within this summary.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure can be better understood with reference to the followingdrawings and description. The components in the figures are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of the disclosure.

FIG. 1 illustrates a block diagram of an infusion system under oneembodiment of the disclosure;

FIG. 2 illustrates a flowchart of one embodiment of a method forinfusing an infusion fluid;

FIG. 3 illustrates a block diagram showing some portions of an infusionsystem under another embodiment of the disclosure;

FIG. 4 illustrates a block diagram showing some portions of an infusionsystem under another embodiment of the disclosure;

FIG. 5 illustrates a flowchart of one embodiment of a method fordetermining confidence levels of air being disposed in an infusionsystem and for determining whether an infusion container has beenemptied of infusion fluid;

FIG. 6 illustrates a graph plotting various confidence regionscorresponding to the confidence regions that air is present in theinfusion system determined using the method of FIG. 5;

FIG. 7 illustrates a block diagram showing some portions of an infusionsystem under another embodiment of the disclosure;

FIG. 8 illustrates a block diagram showing some portions of an infusionsystem under another embodiment of the disclosure;

FIG. 9 illustrates a block diagram showing some portions of an infusionsystem under another embodiment of the disclosure;

FIG. 10 illustrates a graph plotting SPC chart results for oneembodiment of the disclosure using the system of FIG. 8 for end of bagdetection;

FIG. 11 illustrates a block diagram showing some portions of an infusionsystem under another embodiment of the disclosure; and

FIG. 12 illustrates two related graphs illustrating how the use of theinfusion system of FIG. 11 to reconstruct a signal from a wavelettransform effectively determines when the infusion container has run outof infusion fluid.

DETAILED DESCRIPTION

The instant disclosure discloses in part a system and method fordetecting the end-of-infusion (i.e., depletion of fluid in themedication infusion reservoir such as an IV bag or infusion container)for IV medication infusion pumps (e.g., Symbig™, Gemstar™, or Plum™).Current air-in-line detection systems often are not robust and reliableenough to be used routinely as end-of-infusion detectors. Applicant hasdiscovered that the combination of multiple sensors as well as a prioriknowledge about the infusion and medication significantly improves therobustness of detecting an empty medication container via the presenceof air in the line.

The disclosure integrates multiple sensors, drug information and VTBI(volume of the drug in the container to be infused) into the decisionmaking process in order to improve the robustness, and the true negativeand false positive performance of end-of-bag (EOB) detection systems(e.g., qualifies a decision only within VTBI±10%). Disclosed are methodsof qualifying the signals from plunger force sensor and combining theVTBI to improve the reliability of end-of-bag detection systems. Thedisclosed system(s) are designed to function as a redundant safety layerin case of air-sensor based AIL (air-in-line) detection systems fail todetect the EOB. In an alternate embodiment, the disclosure can be usedto detect and quantify the presence of air in the pumping chamber usingmulti-channel filtering, wavelet transforms, neural networks and SPC(Statistical Process Control) charts.

The following is a summary of some distinguishing elements of thedisclosure. In one embodiment of the disclosure, an event detection andqualifier algorithm is disclosed that determines EOB during delivery onthe basis of sensor observations (such as plunger force sensorobservations, air sensor readings, pressure sensor readings) and onother information (such as infusion information or medicationinformation). In another embodiment of the disclosure, an eventdetection algorithm is disclosed that determines confidence levels forpresence of air in the infusion system. In an additional embodiment ofthe disclosure, an event detection algorithm is disclosed thatdetermines the presence of air in the infusion system on the basis ofmulti-channel filtering of the force sensor observations and SPC(Statistical Process Control) charts. In still another embodiment of thedisclosure, an event detection algorithm is disclosed that determinesthe presence of air in the infusion system on the basis of wavelettransform of the force sensor observations and SPC (Statistical ProcessControl) charts. In yet another embodiment of the disclosure, an eventdetection algorithm is disclosed that determines the presence of air inthe infusion system on the basis of non-linear mapping (e.g., neuralnetworks) of sensor observations. In still another embodiment of thedisclosure, quantitative information is provided regarding the volume ofair in a pumping chamber at any particular time.

One problem addressed in the disclosure is to develop a robust end-ofinfusion detection system that will indicate to clinicians when theinfusion container is empty. Another problem addressed in thisdisclosure is to rely on additional information such as infusioninformation or medication information to function as a redundant safetylayer in case sensor based air detection systems fail to detect the EOB.Systems and methods are discloses for qualifying the signals from one ormore sensors and combining the additional information (such as infusioninformation or medication information) to improve the reliability ofend-of bag detection systems.

Another problem addressed in this disclosure is to develop a novelalgorithm (e.g., multi-channel, non-linear mapping such as wavelettransform and neural networks, SPC charts) for detecting air in theinfusion system using sensor observations. In current practice, forcealgorithms are typically based on singe-channel and linear filters.

The disclosure satisfies a customer user need for an accurate andreliable system for detecting the end of an infusion. This is frequentlyobserved at cancer treatment facilities in which nurses spend valuabletime titrating 1-100 mL after the programmed VTBI is complete. Thereason for the additional titration is that infusion bags are typicallyoverfilled by up to 10%.

One embodiment of the disclosure improves the EOB detection capabilityof existing infusion pump systems that rely on sensors to make areal-time assessment. In doing so, the disclosed method does not requireadditional hardware modifications but instead leverages the acquiredmulti-sensor signals. Additionally, the disclosure does not necessarilyreplace existing software modules for air detection but adds anadditional safety layer.

Another embodiment of the disclosure provides a method for improving therobustness of EOB detection systems by reducing the likelihood of afalse positive air detection and by reducing the likelihood of a missedalarm. This reduces the chances of an interruption of therapy due to afalse alarm and also reduces the chances that the system will miss atrue alarm. Still another embodiment of the disclosure provides a meansto improve the sensitivity and specificity of air-in-line detection.

FIG. 1 illustrates a block diagram of an infusion system 100 under oneembodiment of the disclosure. The infusion system 100 comprises: aninfusion container 102; a fluid delivery line 104; a pump device 106; aprocessing device 108; an alarm device 110 that generates an audio,visual, or other sensory signal or the like to a user; an input/outputdevice 112; at least one sensor 114; and a delivery/extraction device116. The infusion system 100 may comprise an infusion system such as thePlum™, Gemstar™ Symbig™, or other type of infusion system.

The infusion container 102 comprises a container for delivering aninfusion fluid such as IV fluid or a drug to a patient 118. The fluiddelivery line 104 comprises one or more tubes, connected between theinfusion container 102, the pump device 106, at least one sensor 114,and the delivery/extraction device 116, for transporting infusion fluidfrom the infusion container 102, through the pump device 106, throughthe at least one sensor 114, through the delivery/extraction device 116to the patient 118. The fluid delivery line 104 may also be used totransport blood, extracted from the patient 118 using thedelivery/extraction device 116, through the at least one sensor 114 as aresult of a pumping action of the pump device 106. The pump device 106comprises a pump for pumping infusion fluid from the infusion container102 or for pumping blood from the patient 118. The pump device 106 maycomprise a plunger based pump, a peristaltic pump, or another type ofpump.

The processing device 108 is in electronic communication with the pumpdevice 106 and the at least one sensor 114. The processing device 108comprises at least one processor for processing information receivedfrom the at least one sensor 114 and for executing one or morealgorithms to determine an air determination related to the air in thefluid delivery line based on measurements taken by the at least onesensor 114 and on: (1) medication information regarding the infusionfluid or infusion information regarding the infusion of the infusionfluid; or (2) multi-channel filtering of the measurements from the atleast one sensor 114 or non-linear mapping of the measurements from theat least one sensor 114; and statistical process control charts appliedto the multi-channel filtered measurements or applied to the non-linearmapped measurements.

The air determination made by the processing device 108 using theprogramming code may be based on: mean values; variances; derivatives;principal component scores; frequencies; wavelet coefficients; shapes;distance metrics; threshold crossings; coherence between signals;correlation between signals; phase shifts; peak values; minimum values;pattern recognition; Bayesian networks; support vector machines; lineardiscriminant analysis; decision trees; K-nearest neighbor; templatematching; thresholds/limits; normalization; digitization; factordecomposition; simple aggregation; or one or more other factors orinformation.

The medication information regarding the infusion fluid delivered fromthe infusion container 102 may comprise a formulation of the infusionfluid, a rate of the infusion fluid, a duration of the infusion fluid, aviscosity of the infusion fluid, a therapy of the infusion fluid, or aproperty of the infusion fluid. The infusion information regarding theinfusion fluid delivered from the infusion container 102 may comprise avolume of the infusion fluid in the infusion container, a volume to beinfused (VTBI), or another parameter regarding the infusion of theinfusion fluid. The processing device 108 includes or is in electroniccommunication with a computer readable memory, containing programmingcode containing the one or more algorithms for execution by theprocessor, and a clock.

The air determination made by the processing device 108 using theprogramming code may comprise determining an end-of-container event whenthe infusion container 102 has been emptied of the infusion fluid,determining a confidence level (which may comprise a probability thatthe infusion system 100 contains the air) that the line 104 of theinfusion system 100 contains the air, or determining whether the air isin the infusion system 100. The processing device 108 may determine theend-of-container event or the confidence level based on the medicationinformation regarding the infusion fluid, based on the infusioninformation regarding the infusion of the infusion fluid, or based on acombination thereof. The processing device 108 may determine whether theair is in the infusion system 100 or to predict or forecast futuremeasurements of the at least one sensor 114 based on the multi-channelfiltering of the measurements from the at least one sensor 114. Theprocessing device 108 may determine whether the air is in the infusionsystem 100 based on the non-linear mapping of the measurements from theat least one sensor 114. In other embodiments, the processing device 108may make the air determination using another type of information basedon any system, method, or other information disclosed herein, or basedon another system, method, or information not disclosed herein.

The alarm device 110 comprises an alarm, triggered by the processingdevice 108, for notifying the clinician (also referred to as ‘user’herein) of: (1) when there is an end-of-container event when theinfusion container 102 has been emptied of the infusion fluid; or (2)when the infusion system 100 contains air. The alarm device 110 may beconfigured to stop the pump device 106 prior to a significant amount ofair being delivered through the fluid delivery line 104 and thedelivery/extraction device 116 to the patient 118.

The input/output device 112 comprises a device which allows a clinicianto input or receive information. The input/output device 112 allows aclinician to input information such as: medication information regardingthe infusion fluid being delivered from the infusion container 102;infusion information regarding the infusion of the infusion fluid beingdelivered from the infusion container 102; the selection of settings forthe processing device 108 to apply in using the programming codecontaining the algorithm(s); or other information that is pertinent tothe infusion. The input/output device 112 may allow a clinician toselect and/or confirm a user-inputted medication infusion program to beapplied by the processing device 108. The input/output device 112 mayfurther output information to the clinician. In other embodiments, anyof the information inputted into the input/output device 112 may bepre-installed into the programming code or the processing device 108. Inanother embodiment, the information may be remotely programmed into theprocessing device 108 from a remote computer or the input/output device112 may be a remote and/or portable computer.

The one or more sensors 114 may comprise any number, combination, orconfiguration of one or more pressure sensors, one or more forcesensors, one or more air sensors, one or more rate sensors, one or moretemperature sensors, or one or more other type of sensors located andconnected to anywhere within the infusion system including the fluiddelivery line 104, the pump device 106, or elsewhere for determiningwhether air is disposed in the infusion system 100. As illustrated thesensor 114 can be located upstream (proximal), downstream (distal) or atthe pump device 106.

If a pressure sensor is used, it may comprise one or more proximal ordistal pressure sensors for detecting the amount of pressure in thefluid delivery line 104 proximal, distal or at the plunger or pumpingmember of the pump device 106. It can also comprise one or more chamberpressure sensors for detecting the amount of pressure in the chamber ofthe pumping device 106. The amount of pressure detected by the one ormore pressure sensors is indicative of whether air, fluid, or somecombination thereof is present in the fluid delivery line 104. Forinstance, U.S. Pat. No. 8,403,908 to Jacobson et al., which is commonlyowned and hereby incorporated by reference, discloses the use ofpressure sensors to determine whether air, fluid, or some combinationthereof is present in the fluid delivery line 104.

If a force sensor is used, it may comprise one or more force sensors(such as a plunger force sensor or other type of sensor) for detectingthe amount of force on the plunger of the pump device 106. The amount offorce detected by the one or more force sensors is indicative of whetherair, fluid, or some combination thereof is present in the fluid deliveryline 104. For instance, U.S. Ser. No. 13/851,207 filed 27 Mar. 2013,which is commonly owned and hereby incorporated by reference, disclosesthe use of force sensors to determine whether air, fluid, or somecombination thereof is present in the fluid delivery line 104.

If an air sensor is used, it may comprise one or more air sensors (suchas a proximal air sensor, a distal air sensor, or another air sensor)for detecting whether air, fluid, or a combination thereof is present inthe fluid delivery line 104. The strength of the signal that propagatesfrom the one or more air sensors through the fluid delivery line 104 isindicative of whether air, fluid, or some combination thereof is presentin the fluid delivery line 104. For instance, U.S. Pat. No. 7,981,082 toWang et al., which is commonly owned and hereby incorporated byreference, discloses the use of air sensors to determine whether air,fluid, or some combination thereof is present in the fluid delivery line104.

If a rate sensor is used, it may comprise one or more rate sensors fordetecting a rate of the infusion fluid traveling through the fluiddelivery line 104 to assist in making the air determination. If atemperature sensor is used, it may comprise one or more temperaturesensors for detecting a temperature of the infusion fluid travelingthrough the fluid delivery line 104 to assist in making the airdetermination. In other embodiments, any number, type, combination, orconfiguration of sensors 114 may be used to determine whether air,fluid, or some combination thereof is present in the fluid delivery line104. For instance, in one embodiment, a plurality of different types ofsensors 114 may be used.

The delivery/extraction device 116 comprises a patient vascular accesspoint device for delivering infusion fluid from the infusion container102 to the patient 118, or for delivering blood to or extracting bloodfrom the patient 118. The delivery/extraction device 116 may comprise aneedle, a catheter, a cannula, or another type of delivery/extractiondevice. In other embodiments, the infusion system 100 of FIG. 1 may bealtered to vary the components, to take away one or more components, orto add one or more components.

FIG. 2 illustrates a flowchart of one embodiment of a method 120 forinfusing an infusion fluid. The method 120 may utilize the infusionsystem 100 of FIG. 1. In other embodiments, the method 120 may utilizevarying systems. In step 122, the infusion fluid is pumped through afluid delivery line of an infusion system. In step 124, measurements aretaken with at least one sensor connected to the infusion system. In step126, at least one processor determines an air determination related towhether air is in the fluid delivery line based on the measurementstaken by the at least one sensor and on: (1) medication informationregarding the infusion fluid or infusion information regarding theinfusion of the infusion fluid; or (2) multi-channel filtering of themeasurements from the at least one sensor or non-linear mapping of themeasurements from the at least one sensor; and statistical processcontrol charts applied to the multi-channel filtered measurements orapplied to the non-linear mapped measurements.

The air determination may comprise determining an end of container eventwhen the infusion container has been emptied of the infusion fluid,determining a confidence level (which may comprise a probability thatthe infusion system contains the air) that the infusion system containsthe air, or determining whether the air is in the infusion system. Themedication information regarding the infusion fluid delivered from theinfusion container may comprise a formulation of the infusion fluid, arate of the infusion fluid, a duration of the infusion fluid, aviscosity of the infusion fluid, a therapy of the infusion fluid, or aproperty of the infusion fluid. The infusion information regarding theinfusion fluid delivered from the infusion container may comprise avolume of the infusion fluid in the infusion container, a volume to beinfused (VTBI), or another parameter regarding the infusion of theinfusion fluid.

In step 128, an alarm device generates or turns on an alarm if step 126determines that air is in the infusion system. Step 128 may furthercomprise the alarm shutting down the infusion system. In otherembodiments, the method 120 may be altered to vary the order orsubstance of any of the steps, to delete one or more steps, or to addone or more steps.

FIG. 3 illustrates a block diagram showing some portions of an infusionsystem 130 under another embodiment of the disclosure. The infusionsystem 130 comprises: an infusion container 132; a fluid delivery line134; a plurality of sensors 136; infusion information 138; medicationinformation 140; an end of infusion detector 142; an end of infusionindicator 144; and a delivery/extraction device 146. For ease ofillustration the pumping device, the processing device/memory, theinput/output device, and the alarm device are not shown in FIG. 3. Theinfusion system 130 may comprise an infusion system such as the Plum™,Gemstar™, Symbig™, or other type of infusion system.

Infusion fluid is delivered from the infusion container 132 through thefluid delivery line 134 through the delivery/extraction device 146 to apatient. The plurality of sensors 136 take measurements during theinfusion. The plurality of sensors 136 may comprise any combination,number, or configuration of one or more plunger force sensor, one ormore proximal air sensor, one or more distal air sensor, one or moreproximal pressure sensor, one or more chamber pressure sensor, one ormore distal pressure sensor, or one or more varying other types ofsensor. The infusion information 138 may comprise a volume of theinfusion fluid in the infusion container 132 or another parameterregarding the infusion of the infusion fluid. The medication information140 may comprise a formulation of the infusion fluid, a rate of theinfusion fluid, a duration of the infusion fluid, a viscosity of theinfusion fluid, a therapy of the infusion fluid, or a property of theinfusion fluid. The infusion information 138 and the medicationinformation 140 may be scanned in, entered by the clinician,auto-programmed, or inputted through varying means.

The end of infusion detector 142 may comprise one or more algorithms tobe applied by programming code of a processing device to determine thatthe infusion container 132 is empty (i.e. the end of the infusion) or todetermine whether or not air, fluid, or some combination thereof ispresent in the infusion system 130. In order to make this determination,the end of infusion detector 142 may rely on the infusion information138, the medication information 140, and on varying features of thesignals of the plurality of sensors 136 such as: mean values; variances;derivatives; principal component scores; frequencies; waveletcoefficients; shapes; distance metrics; threshold crossings; coherencebetween signals; correlation between signals; phase shifts; peak values;minimum values; or one or more other types of features. The end ofinfusion detector 142 may utilize varying methods to combine andclassify the signals of the plurality of sensors 136 such as: patternrecognition; Bayesian networks; support vector machines; lineardiscriminant analysis; decision trees; Knearest neighbor; templatematching; thresholds/limits; normalization; digitization; factordecomposition; simple aggregation; or one or more other factors orinformation.

By using the varying type of information such as the information fromthe plurality of sensors 136, the infusion information 138, and themedication information 140, the end of infusion detector 142determination as to whether or not the infusion container 132 is empty(i.e. the end of the bag, the end of the infusion, etc.) or whether ornot air, fluid, or some combination thereof is contained in the infusionsystem 130 is more accurate and reliable and will lead to less nuisancealarms (when the alarm went off but shouldn't have) or missed alarms(when the alarm should have gone off but didn't). For instance, withoutthe infusion information 138 or the medication information 140, the endof infusion detector 142 may merely rely on the information from thesensors 136 and incorrectly determine that the infusion container 132 isempty because an air slug during delivery has been detected by thesensors 136. However, this may be a temporary situation and the infusioncontainer 132 may not in fact be empty. By relying on this varyinginformation (such as the infusion information revealing that theinfusion container is within 10% or less of being empty when the airslug is detected), the accuracy and reliability of the determination issubstantially increased.

The end of infusion indicator 144 indicates, based on the determinationof the end of infusion detector 142, whether or not the infusioncontainer 132 is empty (i.e. the end of the infusion) or whether or notair, fluid, or some combination thereof is contained in the infusionsystem 130. The end of infusion indicator 144 may turn on an alarmindicating that the infusion container 132 is empty or that air is inthe infusion system 130. The end of infusion indicator 144 may also turnoff the infusion system 130 if the infusion container 132 is empty or ifair is contained in the infusion system 130. In other embodiments, theinfusion system 130 of FIG. 3 may be altered to vary the components, totake away one or more components, or to add one or more components.

FIG. 4 illustrates a block diagram showing some portions of an infusionsystem 150 under another embodiment of the disclosure. The infusionsystem 150 comprises: one or more sensors 152; infusion information 154;an end of infusion detector 156; and an end of infusion indicator 158.For ease of illustration the infusion container, the fluid deliveryline, the pumping device, the processing device/memory, the input/outputdevice, the delivery/extraction device, and the alarm device are notshown in FIG. 4. The infusion system 150 may comprise an infusion systemsuch as the Plum™, Gemstar™, Symbig™, or other type of infusion system.

The one or more sensors 152 take measurements during the infusion. Theone or more sensors 152 may comprise any combination, number, orconfiguration of one or more plunger force sensor, one or more proximalair sensor, one or more distal air sensor, one or more proximal pressuresensor, one or more chamber pressure sensor, one or more distal pressuresensor, or one or more varying other types of sensor. The infusioninformation 154 may comprise a volume of the infusion fluid in theinfusion container, volume to be infused (VTBI), or another parameterregarding the infusion of the infusion fluid. The infusion information154 may be scanned in, entered by the clinician, auto-programmed, orinputted through varying means.

The end of infusion detector 156 may comprise one or more algorithms tobe applied by programming code of a processing device to determine thatthe infusion container is empty (i.e. the end of the infusion) or todetermine whether or not air, fluid, or some combination thereof iscontained in the infusion system 150. In order to make thisdetermination, the end of infusion detector 156 may rely on themeasurements taken by the one or more sensors 152 and on the infusioninformation 154.

By using the varying type of information such as the information fromthe one or more sensors 152 and the infusion information 154, the end ofinfusion detector 156 makes a determination as to whether or not theinfusion container is empty (i.e. the end of the bag, the end of theinfusion, etc.) or whether or not air, fluid, or some combinationthereof is contained in the infusion system 150. This determination ismore accurate and reliable and will lead to less nuisance alarms (whenthe alarm went off but shouldn't have) or missed alarms (when the alarmshould have gone off but didn't) due to the use of the varyinginformation.

The end of infusion indicator 158 indicates, based on the determinationof the end of infusion detector 156, whether or not the infusioncontainer is empty (i.e. the end of the infusion) or whether or not air,fluid, or some combination thereof is contained in the infusion system150. The end of infusion indicator 158 may turn on an alarm indicatingthat the infusion container is empty or that air is in the infusionsystem 150. The end of infusion indicator 158 may also turn off theinfusion system 150 if the infusion container is empty or if air iscontained in the infusion system 150. In other embodiments, the infusionsystem 150 of FIG. 4 may be altered to vary the components, to take awayone or more components, or to add one or more components. For instance,in another embodiment instead of relying on the measurements of one ormore sensor and on the infusion information, the end of infusiondetector may rely on the measurements of one or more sensor and on themedication information. In other embodiments, the end of infusiondetector may rely on varying combinations of information.

FIG. 5 illustrates a flowchart of one embodiment of a method 160 fordetermining confidence levels of air being disposed in an infusionsystem and for determining whether an infusion container has beenemptied of infusion fluid. It can be applied to any air-in-linealgorithm as long as it outputs a force profile at each sampling step(throughout this disclosure the term ‘sampling step’ corresponds to thecurrent pumping cycle and the term ‘previous sampling step’ correspondsto the previous pumping cycle) and as long as it keeps track of how manystrokes the pumping cycle has undergone. The method 160 determines ateach sampling step a force difference between the force profile and abaseline, and also determines the total volume of infusion fluid infusedto present. The method 160 compares the force difference at eachsampling step to multiple thresholds for air detection and based onwhere the force difference falls relative to the multiple thresholdsdetermines a confidence level of air being contained in the infusionsystem. If the confidence level is between 80 to 100 percent that air iscontained in the infusion system then the method 160 determines whetherthe total volume of infusion fluid which has been infused is within 10%of the total volume of infusion fluid contained within the infusioncontainer. If it is, then the method 160 determines that the containerhas been emptied of the infusion fluid (i.e. the end of bag has beenreached) and turns on an alarm to notify the user and/or to shut downthe infusion system. By using varying types of information (i.e.infusion information such as the total volume of infusion fluid to beinfused, and the sensor measurement information) the accuracy andreliability of the end of bag detection is increased. The method 160 mayutilize the system of FIG. 1. In other embodiments, the method 160 mayutilize varying systems.

In step 162, the method starts. The method proceeds from step 162 tostep 164. In step 164, the variables are set including setting samplingstep k=0, setting the initial force profile X(0) associated with fluid,setting a Baseline force profile for fluid, setting a first thresholdThr1 for air detection (for instance by setting Thr1=−0.3 pounds in oneembodiment), setting a second threshold Thr2 for air detection (forinstance by setting Thr2=−0.6 pounds in one embodiment), setting aforgetting factor A (for instance by setting A=0.1), setting a strokevolume Stroke Vol delivered by one stroke (for instance by settingStroke Vol=0.075 ml), and by setting a volume to be infused VTBI (forinstance a user-specified volume such as 500 ml). It is noted that theBaseline force profile for fluid represents a Baseline plurality offorce readings representing the Baseline force profile at each stroke kof the pump. For instance, in one embodiment the Baseline force profilemay comprise six representative force readings representing fluid at sixpoints of a stroke k of the pump. In other embodiments, the Baselineforce profile may comprise any number of representative force readingsrepresenting fluid at various points of the stroke k of the pump. Thefirst threshold Thr1, the second threshold Thr2, and the Baseline can beset to universal values or set for the particular type of medication tobe infused.

The method proceeds from step 164 through location step 166 to step 168.In step 168, the baseline is updated using the equationBaseline=(1−A)*Baseline+A*X(k). By updating the Baseline at each cyclewith an exponentially weighted forgetting factor, variability in theforce profiles due to medication type, tubing type, pump motor control,ambient temperature, etc. may be accounted for. The method proceeds fromstep 168 to step 170. In step 170, the sampling step k is incrementedusing the equation k=k+1. The method proceeds from step 170 to step 172.In step 172, a force profile X(k) for the current sampling step k isacquired. It is noted that the force profile X(k) represents a pluralityof force readings which are taken during each stroke k of the pump. Forinstance, in one embodiment six force readings may be taken at variouspoints of each stroke k of the pump. In other embodiments, any number offorce readings may be taken throughout each stroke k of the pump. Themethod proceeds from step 172 through location step 174 to step 176.

While the method proceeds from step 170 to step 172, the method alsosimultaneously proceeds from step 170 to step 178. In step 178, thetotal volume infused as of the present sampling step k is calculatedusing the equation InfVol=k*Stroke Vol. The method proceeds from step178 through location step 174 to step 176.

In step 176, the force difference D(k) at the current sampling step k isdetermined using the equation D(k)=X(k)−Baseline. Since the forceprofile X(k) and the Baseline each comprise a plurality of forcereadings this force difference will be a vector. The method proceedsfrom step 176 to step 180. In step 180, a determination is made as towhether the minimum value of the force difference min(D(k)) (i.e. theminimum value in the force difference vector) at the current samplingstep k is less than the second threshold Thr2 using the equationmin(D(k))<Thr2. If a determination is made in step 180 that the minimumvalue of the force difference min(D(k)) is not less than Thr2 (i.e. ifmin(D(k))≥Thr2) then the method proceeds from step 180 to step 182. Instep 182, a determination is made as to whether the minimum value of theforce difference min(D(k)) (i.e. the minimum value in the forcedifference vector) at the current sampling step k is greater than orequal to the second threshold Thr2 and less than or equal to the firstthreshold Thr1 using the equation Thr2≤min(D(k))≤Thr1. If adetermination is made in step 182 that the minimum value of the forcedifference min(D(k)) at the current sampling step k is not greater thanor equal to the second threshold Thr2 and less than or equal to thefirst threshold Thr1 (i.e. if either min(D(k))<Thr2 or ifmin(D(k))>Thr1) then the method proceeds from step 182 to step 184. Instep 184, the confidence level Conf that there is air in the infusionsystem is set in the range of 0% to 40%. The method proceeds from step184 through location step 186 through location step 166 to step 168 andrepeats the process steps.

If a determination is made in step 182 that the minimum value of theforce difference min(D(k)) at the current sampling step k is greaterthan or equal to the second threshold Thr2 and less than or equal to thefirst threshold Thr1 (i.e. if min(D(k))≥Thr2 and if min(D(k))≥Thr1) thenthe method proceeds from step 182 to step 188. In step 188, adetermination is made as to whether the minimum force differencemin(D(k−1)) at the preceding sampling step k−1 (i.e. the minimum valuein the force difference vector at sampling step k−1) is less than orequal to the first threshold Thr1 using the equation min(D(k−1))≤Thr1.If the determination is made in step 188 that the minimum forcedifference min(D(k−1)) at the preceding sampling step k−1 is not lessthan or equal to the first threshold Thr1 (i.e. min(D(k−1))>Thr1) thenthe method proceeds from step 188 to step 184. In step 184, theconfidence level Conf that there is air in the infusion system is set inthe range of 0% to 40%. The method proceeds from step 184 throughlocation step 186 through location step 166 to step 168 and repeats theprocess steps.

If a determination is made in step 188 that the minimum force differencemin(D(k−1)) at the preceding sampling step k−1 is less than or equal tothe first threshold Thr1 (i.e. min(D(k−1))≤Thr1) then the methodproceeds from step 188 to step 190. In step 190, the confidence levelConf that there is air in the infusion system is set in the range of 60%to 80%. The method proceeds from step 190 through location step 192through location step 166 to step 168 and repeats the process steps.

If a determination is made in step 180 that min(D(k)) is less than Thr2(i.e. if min(D(k))<Thr2) then the method proceeds from step 180 to step194. In step 194, a determination is made as to whether the minimumforce difference min(D(k−1)) at the preceding sampling step k−1 (i.e.the minimum value in the force difference vector at sampling step k−1)is less than or equal to the first threshold Thr1 using the equationmin(D(k−1))<Thr1. If a determination is made in step 194 that theminimum force difference min(D(k−1)) at the preceding sampling step k−1is not less than or equal to the first threshold Thr1 (i.e. ifmin(D(k−1))>Thr1) then the method proceeds from step 194 to step 196. Instep 196, the confidence level Conf that there is air in the infusionsystem is set in the range of 40% to 60%. The method proceeds from step196 through location step 198 through location step 166 to step 168 andrepeats the process steps.

If a determination is made in step 194 that the minimum force differencemin(D(k−1)) at the preceding sampling step k−1 is less than or equal tothe first threshold Thr1 (i.e. if min(D(k−1))≤Thr1) then the methodproceeds from step 194 to step 200. In step 200, the confidence levelConf that there is air in the infusion system is set in the range of 80%to 100%. The method proceeds from step 200 to step 202. In step 202, adetermination is made as to whether the total volume infused to presentInfVol is within 10% of the total volume of the infusion fluid to beinfused VTBI using the equation InfVol=VTBI±10%. If the determination ismade in step 202 that the total volume infused to present InfVol is notwithin 10% of the total volume of the infusion fluid to be infused VTBI(i.e. InfVol:it VTBI±10%) then the method proceeds from step 202 throughlocation step 204 through location step 166 to step 168 and repeats theprocess steps. It is noted that even though there is a high confidencelevel in a range of 80% to 100% that air is contained in the infusionsystem, that since the volume of infusion fluid infused to present isnot within 10% of the total volume to be infused that the air in thesystem must be due to one or more slugs of air and is not due to an endof container (end of bag) event.

If the determination is made in step 202 that the total volume infusedto present InfVol is within 10% of the total volume of the infusionfluid to be infused VTBI (i.e. InfVol=VTBI±10%) then the method proceedsfrom step 202 to step 206. In step 206, an end of container event (i.e.end of bag event) is detected in which the infusion container has beenemptied of the infusion fluid. It is important to note that since theminimum of the force difference min(D(k)) for the current sampling stepk is less than the second threshold Thr2, the minimum of the forcedifference min(D(k−1)) for the preceding sampling step k−1 is less thanor equal to the first threshold Thr1, and the total volume infused topresent InfVol is within 10% of the total volume of the infusion fluidto be infused InfVol that the determination that the end of thecontainer has been reached is highly accurate and reliable. The methodproceeds from step 206 to step 208. In step 208, the alarm is turned onindicating that the infusion container has been emptied of the infusionfluid. When the alarm is generated or turned on in step 208, theinfusion system may be turned off automatically or manually by the userto stop the infusion of the infusion fluid.

In other embodiments, the method 160 may be altered to vary the order orsubstance of any of the steps, to delete one or more of the steps, or toadd one or more steps. For instance, instead of using force sensormeasurements, one or more other types of sensors may be used (i.e.pressure, air, rate, temperature, etc.) and instead of using theinfusion information comprising the volume to be infused (VTBI) one ormore other types of information may be used (i.e. other types ofinfusion information as disclosed herein, medication information asdisclosed herein, etc.). In still other embodiments, any number, type,and configuration of sensor information, infusion information,medication information, or other types of information may be used.

FIG. 6 illustrates a graph 210 plotting various confidence regionscorresponding to the confidence regions that air is in the infusionsystem determined using the method 160 of FIG. 5. Plotted on the X-axisis the minimum force difference D(k) at the current sampling step k withD(k)=X(k)−Baseline as discussed in FIG. 5. Plotted on the Y-axis is theminimum force difference D(k−1) at the previous sampling step k−1 withD(k−1)=X(k−1)−Baseline as discussed in FIG. 5. The first threshold Thr1is −0.3 pounds. The second threshold Thr2 is −0.6 pounds.

As shown, confidence region 162 represents having a confidence level ina range of 80% to 100% that air is in the infusion system. In confidenceregion 162 one of the following is true: (i) in two consecutive samplingsteps (cycles) k−1 and k the minimum force difference D(k−1) and D(k)was less than the second threshold Thr2 (e.g. the last two drops in theforce reading were very large in magnitude); or (ii) in the currentsampling step k the minimum force difference D(k) is less than thesecond threshold Thr2 and the minimum force difference D(k−1) for thepreceding sampling step k−1 was between the second threshold Thr2 andthe first threshold Thr1 (e.g. the current drop in force reading is verylarge and the previous drop was large in magnitude). It is noted thatfluid is less compressible than air so when transitioning from fluid toair a drop in the force profile X(k) and correspondingly a drop in theforce difference D(k) is expected.

Confidence region 164 represents having a confidence level in a range of60% to 80% that air is in the infusion system. In confidence region 164one of the following is true: (i) in two consecutive sampling steps(cycles) k−1 and k the minimum force difference D(k−1) and D(k) isbetween the second threshold Thr2 and the first threshold Thr1 (e.g. thelast two drops in force readings were large); or (ii) the currentminimum force difference D(k) is between the second threshold Thr2 andthe first threshold Thr1 and the previous minimum force differenceD(k−1) was lower than the second threshold Thr2 (e.g. the current dropin force reading is large and the previous drop in force reading wasvery large).

Confidence region 166 represents having a confidence level in a range of40% to 60% that air is in the infusion system. In confidence region 166the current minimum force difference D(k) is lower than the secondthreshold Thr2 and the previous minimum force difference D(k−1) washigher than the first threshold Thr1 (e.g. the current drop in forcereading is very large and the previous drop in force reading was smallor non-existent).

Confidence region 168 represents having a confidence level in a range of0% to 40% that air is in the infusion system. In confidence region 168one of the following is true: (i) the current minimum force differenceD(k) is higher than the first threshold Thr1 (e.g. the current drop inforce reading is very small or non-existent); or (ii) the currentminimum force difference D(k) is between the second threshold Thr2 andthe first threshold Thr1 and the previous minimum force differenceD(k−1) was higher than the first threshold Thr1 (e.g. the current dropin force reading is large and the previous drop in force reading wassmall or non-existent). In other embodiments, the algorithms used by themethod 160 of FIG. 5 can be changed so that the number of thresholds andconfidence regions can be varied depending on whether more or lesssensitivity is desired.

FIG. 7 illustrates a block diagram showing some portions of an infusionsystem 170 under another embodiment of the disclosure. The infusionsystem 170 comprises: a sensor 172; a plurality of filters 174; one ormore statistical process control (SPC) charts 176; information 178; oneor more qualifiers 180; and an alarm device 182. For ease ofillustration the infusion container, the fluid delivery line, thepumping device, the processing device/memory, the input/output device,and the delivery/extraction device are not shown in FIG. 7. The infusionsystem 170 may comprise an infusion system such as the Plum™ Gemstar™,Symbig™, or other type of infusion system.

The sensor 172 comprises a plunger force sensor which takes measurementsduring the infusion. In other embodiments, the sensor 172 may compriseany combination, number, or configuration of one or more plunger forcesensors, one or more proximal air sensors, one or more distal airsensors, one or more proximal pressure sensors, one or more chamberpressure sensors, one or more distal pressure sensors, or one or morevarying other type of sensors.

The plurality of filters 174 comprises a Kalman filter for estimatingmean force based on the measurements of the sensor 172, a second Kalmanfilter for estimating variance force based on the measurements of thesensor 172, and a third Kalman filter for estimating derivative forcebased on the measurements of the sensor 172. In other embodiments, anynumber, type, and configuration of filters may be used to filter themeasurements of the sensor 172 to determine varying informationregarding the measurements of the sensor 172.

The one or more SPC charts 176 may comprise any number and type of SPCchart which are constructed based on the forecasted n-steps aheadfiltered measurements of the sensor 172. For instance, a cumulative sumcontrol chart (CUSUM), an exponentially weighted moving average controlchart (EWMA), or other types of charts may be constructed based on theforecasted n-steps ahead filtered measurements of the sensor 172.

The information 178 comprises infusion information comprising the volumeof the infusion fluid in the infusion container. In other embodiments,the information may comprise varying types of infusion information, maycomprise medication information, or may comprise one or more other typesof information. The medication information may comprise a formulation ofthe infusion fluid, a rate of the infusion fluid, a duration of theinfusion fluid, a viscosity of the infusion fluid, a therapy of theinfusion fluid, or a property of the infusion fluid. In otherembodiments, one or more other type of information may be used.

The qualifier 180 may comprise one or more algorithms to be applied byprogramming code of a processing device to determine that the infusioncontainer is empty (i.e. the end of the infusion) or to determinewhether or not air, fluid, or some combination thereof is contained inthe infusion system 170. In order to make this determination, thequalifier 180 may rely on the constructed SPC charts 176 and on theinformation 178. This determination is more accurate and reliable andwill lead to less nuisance alarms (when the alarm went off but shouldn'thave) or missed alarms (when the alarm should have gone off but didn't)due to the use of the varying types of information used. In otherembodiments, the qualifier 180 may rely on varying information to makethe determination.

The alarm device 182 may generate or turn on an alarm to indicate thatthe infusion container is empty if the qualifier 180 determines that theinfusion container is empty or if it determines that air is contained inthe infusion system. In this event, the alarm device 182 may furtherautomatically or manually turn off the infusion system to stop theinfusion. In other embodiments, the infusion system 170 of FIG. 7 may bealtered to vary the components, to take away one or more components, orto add one or more components.

FIG. 8 illustrates a block diagram showing some portions of an infusionsystem 190 under another embodiment of the disclosure. The infusionsystem 190 comprises: a sensor 192; a plurality of filters 194; one ormore statistical process control (SPC) charts 196; information 198; oneor more qualifiers 200; and an alarm device 202. For ease ofillustration the infusion container, the fluid delivery line, thepumping device, the processing device/memory, the input/output device,and the delivery/extraction device are not shown in FIG. 8. The infusionsystem 190 may comprise an infusion system such as the Plum™ Gemstar™,Symbig™, or other type of infusion system.

The sensor 192 comprises a plunger force sensor which takes measurementsduring the infusion. In other embodiments, the sensor 192 may compriseany combination, number, or configuration of one or more plunger forcesensors, one or more proximal air sensors, one or more distal airsensors, one or more proximal pressure sensors, one or more chamberpressure sensors, one or more distal pressure sensors, or one or morevarying other type of sensors.

The plurality of filters 194 comprises a Kalman filter for estimatingmean force based on the measurements of the sensor 192, a second Kalmanfilter for estimating variance force based on the measurements of thesensor 192, and a third Kalman filter for estimating derivative forcebased on the measurements of the sensor 192. In other embodiments, anynumber, type, and configuration of filters may be used to filter themeasurements of the sensor 192 to determine varying informationregarding the measurements of the sensor 192.

The one or more SPC charts 196 may comprise any number and type of SPCchart which are constructed based on the residuals of the filteredmeasurements of the sensor 192. The residual is defined as thedifference between the actual signal characteristic as measured (forinstance the actual plunger force measurement) and theestimated/expected/anticipated signal characteristic via the filtering(for instance the estimated/expected/anticipated plunger forcemeasurement as a result of the filtering). A cumulative sum controlchart (CUSUM), an exponentially weighted moving average control chart(EWMA), or other types of charts may be constructed based on theresiduals of the filtered measurements of the sensor 192.

The information 198 comprises infusion information comprising the volumeof the infusion fluid in the infusion container. In other embodiments,the information may comprise varying types of infusion information, maycomprise medication information, or may comprise one or more other typesof information. The medication information may comprise a formulation ofthe infusion fluid, a rate of the infusion fluid, a duration of theinfusion fluid, a viscosity of the infusion fluid, a therapy of theinfusion fluid, or a property of the infusion fluid. In otherembodiments, one or more other type of information may be used.

The qualifier 200 may comprise one or more algorithms to be applied byprogramming code of a processing device to determine that the infusioncontainer is empty (i.e. the end of the infusion) or to determinewhether or not air, fluid, or some combination thereof is contained inthe infusion system 190. In order to make this determination, thequalifier 200 may rely on the constructed SPC charts 196 and on theinformation 198. This determination is more accurate and reliable andwill lead to less nuisance alarms (when the alarm went off but shouldn'thave) or missed alarms (when the alarm should have gone off but didn't)due to the use of the varying types of information used. In otherembodiments, the qualifier 200 may rely on varying information to makethe determination.

The alarm device 202 may generate or turn on an alarm to indicate thatthe infusion container is empty if the qualifier 200 determines that theinfusion container is empty or if it determines that air is contained inthe infusion system. In this event, the alarm device 202 may furtherautomatically or manually turn off the infusion system to stop theinfusion. In other embodiments, the infusion system 190 of FIG. 8 may bealtered to vary the components, to take away one or more components, orto add one or more components.

FIG. 9 illustrates a block diagram showing some portions of an infusionsystem 210 under another embodiment of the disclosure. The infusionsystem 210 comprises: a plurality of sensors 212; a plurality of filters214; one or more statistical process control (SPC) charts 216;information 218; one or more qualifiers 220; and an alarm device 222.For ease of illustration the infusion container, the fluid deliveryline, the pumping device, the processing device/memory, the input/outputdevice, and the delivery/extraction device are not shown in FIG. 9. Theinfusion system 210 may comprise an infusion system such as the Plum™,Gemstar™, Symbig™, or other type of infusion system.

The plurality of sensors 212 comprise an air sensor, a pressure sensor,a force sensor, and any number and type of other sensors that aredesired to take measurements during the infusion. In other embodiments,any number, type, and configuration of sensors may be used to takemeasurements during the infusion.

The plurality of filters 214 comprises a Kalman filter for estimatingmean force based on the measurements of the sensors 212, a second Kalmanfilter for estimating variance force based on the measurements of thesensors 212, and a third Kalman filter for estimating derivative forcebased on the measurements of the sensors 212. In other embodiments, anynumber, type, and configuration of filters may be used to filter themeasurements of the sensors 212 to determine varying informationregarding the measurements of the sensors 212.

The one or more SPC charts 216 may comprise any number and type of SPCchart which are constructed based on the residuals of the filteredmeasurements of the plurality of sensors 212. The residual is defined asthe difference between the actual signal characteristic as measured (forinstance the actual plunger force measurement) and theestimated/expected/anticipated signal characteristic via the filtering(for instance the estimated/expected/anticipated plunger forcemeasurement as a result of the filtering). A cumulative sum controlchart (CUSUM), an exponentially weighted moving average control chart(EWMA), or other types of charts may be constructed based on theresiduals of the filtered measurements of the plurality of sensors 212.

The information 218 comprises infusion information comprising the volumeof the infusion fluid in the infusion container or the volume to beinfused (VBTI). In other embodiments, the information may comprisevarying types of infusion information, may comprise medicationinformation, or may comprise one or more other types of information. Themedication information may comprise a formulation of the infusion fluid,a rate of the infusion fluid, a duration of the infusion fluid, aviscosity of the infusion fluid, a therapy of the infusion fluid, or aproperty of the infusion fluid. In other embodiments, one or more othertype of information may be used.

The qualifier 220 may comprise one or more algorithms to be applied byprogramming code of a processing device to determine that the infusioncontainer is empty (i.e. the end of the infusion) or to determinewhether or not air, fluid, or some combination thereof is contained inthe infusion system 210. In order to make this determination, thequalifier 220 may rely on the constructed SPC charts 216 and on theinformation 218. This determination is more accurate and reliable andwill lead to less nuisance alarms (when the alarm went off but shouldn'thave) or missed alarms (when the alarm should have gone off but didn't)due to the use of the varying types of information used. In otherembodiments, the qualifier 220 may rely on varying information to makethe determination.

The alarm device 222 may turn on an alarm to indicate that the infusioncontainer is empty if the qualifier 220 determines that the infusioncontainer is empty or if it determines that air is contained in theinfusion system. In this event, the alarm device 222 may furtherautomatically or manually turn off the infusion system to stop theinfusion. In other embodiments, the infusion system 210 of FIG. 9 may bealtered to vary the components, to take away one or more components, orto add one or more components.

FIG. 10 illustrates a graph 230 plotting SPC chart results for oneembodiment of the disclosure using the system of FIG. 8 for end of bagdetection (i.e. end of the infusion fluid in the infusion container).Plotted on the X-axis is the stroke number (also referred to as thesampling step herein) for the pump. Plotted on the Y-axis is a CUSUM SPCchart. The graph 230 was plotted based on the residuals (i.e. thedifference) between the actual mean force of the signals measured by thesensors of FIG. 8 and the Kalman filter estimated mean force per pumpingstroke during a test run on a Symbig™ pump using the system of FIG. 8.

Line 232 represents the lower control limit. Line 234 represents theupper control limit. Curve 236 represents the lower CUSUM that is thecumulative sum in the negative direction. Curve 238 represents the upperCUSUM that is the cumulative sum in the positive direction. Out ofcontrol area 240 represents an area where curve 236 drops below thelower control limit 232 and substantially deviates from curve 238 whichclearly indicates that the infusion container has run out of infusionfluid (i.e. the end of the bag). This determination is buttressedbecause not only were the SPC charts constructed based on the sensormeasurements but also infusion information was utilized ensuring thatout of control area 240 is within 10% of the total volume of theinfusion fluid in the infusion container. This provides increasedaccuracy to the determination, and reduces the risk of a nuisance alarmor a missed alarm.

FIG. 11 illustrates a block diagram showing some portions of an infusionsystem 250 under another embodiment of the disclosure. The infusionsystem 250 comprises: a sensor 252; a wavelet transform block 254; oneor more statistical process control (SPC) charts 256; information 258;one or more qualifiers 260; and an alarm device 262. For ease ofillustration the infusion container, the fluid delivery line, thepumping device, the processing device/memory, the input/output device,and the delivery/extraction device are not shown in FIG. 11. Theinfusion system 250 may comprise an infusion system such as the Plum™,Gemstar™, Symbig™, or other type of infusion system.

The sensor 252 comprises a plunger force sensor which takes measurementsduring the infusion. In other embodiments, the sensor 252 may compriseany combination, number, or configuration of one or more plunger forcesensors, one or more proximal air sensors, one or more distal airsensors, one or more proximal pressure sensors, one or more chamberpressure sensors, one or more distal pressure sensors, or one or morevarying other type of sensors.

The wavelet transform block 254 comprises a wavelet decomposition block254 a, a coefficient threshold block 254 b, and a signal reconstructionblock 254 c. The wavelet decomposition block 254 a decomposes thewavelet based on the plunger force sensor signal to obtain the waveletcoefficients. The coefficient threshold block 254 b applies one or morethresholds to the obtained wavelet coefficients to remove the noise. Thesignal reconstruction block 254 c applies an inverse wavelet transformto the threshold coefficients to obtain a de-noised signal. In otherembodiments, any number, type, and configuration of wavelet transformblocks may be applied to the measurements of the sensor 252 to determinevarying information regarding the measurements of the sensor 252.

The one or more SPC charts 256 may comprise any number and type of SPCchart which are constructed based on the de-noised signal obtained usingthe wavelet transform block 254. A cumulative sum control chart (CUSUM),an exponentially weighted moving average control chart (EWMA), or othertypes of charts may be constructed based on the de-noised signalobtained using the wavelet transform block 254.

The information 258 comprises infusion information comprising the volumeof the infusion fluid in the infusion container. In other embodiments,the information may comprise varying types of infusion information, maycomprise medication information, or may comprise one or more other typesof information. The medication information may comprise a formulation ofthe infusion fluid, a rate of the infusion fluid, a duration of theinfusion fluid, a viscosity of the infusion fluid, a therapy of theinfusion fluid, or a property of the infusion fluid. In otherembodiments, one or more other type of information may be used.

The qualifier 260 may comprise one or more algorithms to be applied byprogramming code of a processing device to determine that the infusioncontainer is empty (i.e. the end of the infusion) or to determinewhether or not air, fluid, or some combination thereof is contained inthe infusion system 250. In order to make this determination, thequalifier 260 may rely on the constructed SPC charts 256 and on theinformation 258. This determination is buttressed because not only werethe wavelet transform block used to construct SPC charts based on theplunger force sensor signal measurements but also infusion informationwas utilized ensuring that the out of control area was within a presetpercentage of the total volume of the infusion fluid in the infusioncontainer (e.g. 10% of the total volume of the infusion fluid in theinfusion container). This determination is more accurate and reliableand will lead to less nuisance alarms (when the alarm went off butshouldn't have) or missed alarms (when the alarm should have gone offbut didn't) due to the use of the varying types of information used. Inother embodiments, the qualifier 260 may rely on varying information tomake the determination.

The alarm device 262 may generate or turn on an alarm to indicate thatthe infusion container is empty if the qualifier 260 determines that theinfusion container is empty or if it determines that air is contained inthe infusion system. In this event, the alarm device 262 may furtherautomatically or manually turn off the infusion system to stop theinfusion. In other embodiments, the infusion system 250 of FIG. 11 maybe altered to vary the components, to take away one or more components,or to add one or more components. For instance, in another embodimentthe wavelet transform block 254 can be replaced by a neural networkblock.

FIG. 12 illustrates two related graphs 270 and 272 illustrating how theuse of the infusion system of FIG. 11 to reconstruct a signal from awavelet transform effectively determines when the infusion container hasrun out of infusion fluid. Graph 270 plots the original raw signalobtained using the sensor of FIG. 11 in a Symbig™ pump. The X-axis ofgraph 270 represents sample number of the pump cycles of the infusionsystem. The Y-axis of graph 270 represents the plunger force in poundsexerted on the plunger during the pumping of the infusion cycles. Atarea 274 there is an end of bag event in which the infusion containerhas been emptied of the infusion fluid. At area 27 4, the plunger forcedecreases slightly due to the decreased level of force applied to theplunger by air relative to fluid.

Graph 272 plots the reconstructed signal from the wavelet transformusing the infusion system of FIG. 11. The X-axis of graph 272 representssample number of the pump cycles of the infusion system. The Y-axis ofgraph 272 represents the plunger force in pounds exerted on the plungerduring the pumping of the infusion cycles. At area 276 of graph 272,which corresponds to area 274 of graph 270, there is the same end of bagevent in which the infusion container has been emptied of the infusionfluid. At area 276, the plunger force decreases greatly and is much moredetectable then area 274 of graph 270 as a result of the application ofthe reconstructed signal from the wavelet transform using the infusionsystem of FIG. 11. This illustrates how applying the wavelet transformblock to the measured signals of the sensor makes it much easier todetect an end of bag event, in addition to being much more reliable andaccurate due to the varying types of information relied upon as detailedabove.

All of the embodiments of the disclosure can be used to determine thepresence of air in the pumping chamber and provide AIL (air-in-line)alarms. This can easily be achieved by excluding the information such asvolume to the end of bag (VTBI) or other infusion information ormedication information from the qualifier block(s). In current practice,the force algorithms developed to detect the presence of air in thechamber are typically based on singe-channel and linear filters/methods.However, the instant disclosure discloses systems and methods thatutilize multi-channel filtering, non-linear mapping such as wavelettransform and neural networks, and SPC charts.

Alternate methodologies can be used to combine the diverse informationprovided by the varying sensors (such as force sensors, air sensors, andpressure sensors) and the additional information supplied such as theinfusion information, the medication information, or other types ofinformation. One such methodology comprises the application of arule-based system that encompasses expert knowledge concerning thecombination of events leading to the probability of an end-of-infusionevent.

In another embodiment, a machine learning methodology may be used inwhich one or more pattern recognition systems are used to detect an endof infusion event on the basis of features extracted from the dataelements. For this purpose, both parametric (linear discriminantanalysis, support vector machines, artificial neural networks, logisticregression, Bayesian networks, dynamic Bayesian networks, etc.) andnonparametric (k-nearest-neighbor, decision trees, etc.) methods providepotential alternatives. This approach provides the option to uncover andlearn complex patterns which occur through time to detect the likelihoodof an end of infusion event.

The Abstract is provided to allow the reader to quickly ascertain thenature of the technical disclosure. It is submitted with theunderstanding that it will not be used to interpret or limit the scopeor meaning of the claims. In addition, in the foregoing DetailedDescription, it can be seen that various features are grouped togetherin various embodiments for the purpose of streamlining the disclosure.This method of disclosure is not to be interpreted as reflecting anintention that the claimed embodiments require more features than areexpressly recited in each claim. Rather, as the following claimsreflect, inventive subject matter lies in less than all features of asingle disclosed embodiment. Thus the following claims are herebyincorporated into the Detailed Description, with each claim standing onits own as a separately claimed subject matter.

While particular aspects of the present subject matter described hereinhave been shown and described, it will be apparent to those skilled inthe art that, based upon the teachings herein, changes and modificationsmay be made without departing from the subject matter described hereinand its broader aspects and, therefore, the appended claims are toencompass within their scope all such changes and modifications as arewithin the true scope of the subject matter described herein.Furthermore, it is to be understood that the disclosure is defined bythe appended claims. Accordingly, the disclosure is not to be restrictedexcept in light of the appended claims and their equivalents.

1.-20. (canceled)
 21. An infusion system configured to be connected to afluid delivery line and to an infusion container containing an infusionfluid, the infusion system comprising: a pump; at least one sensorconnected to the pump or the fluid delivery line, the at least onesensor configured to indicate whether air is in the fluid delivery line;at least one processor in electronic communication with the pump and theat least one sensor; a memory in electronic communication with the atleast one processor, the memory comprising programming code forexecution by the at least one processor; and wherein the programmingcode is configured to cause the at least one processor to determine anair determination related to the air in the fluid delivery line based onstatistical process control charts applied to multi-channel filteredmeasurements from the at least one sensor.
 22. The infusion system ofclaim 21, wherein the at least one sensor comprises a plunger forcesensor, the plunger force sensor positioned on the pump.
 23. Theinfusion system of claim 21, wherein the multi-channel filteredmeasurements comprise measurements filtered by a plurality of Kalmanfilters.
 24. The infusion system of claim 23, wherein the plurality ofKalman filters comprise: a first Kalman filter configured to estimatemean force, a second Kalman filter configured to estimate varianceforce, and a third Kalman filter configured to estimate derivativeforce.
 25. The infusion system of claim 21, wherein the statisticalprocess control charts comprise a calculation of a residual value, theresidual value comprising the difference between an actual signalcharacteristic measured by the at least one sensor and a predictedsignal characteristic of the signal measured by the at least one sensor.26. The infusion system of claim 25, wherein the statistical processcontrol charts comprise a cumulative sum control chart.
 27. The infusionsystem of claim 26, wherein the cumulative sum control chart comprises acumulative sum of the residual values in a positive direction and acumulative sum of the residual values in a negative direction.
 28. Theinfusion system of claim 21, wherein the statistical process controlcharts comprise an exponentially moving average control chart.
 29. Aninfusion system configured to be connected to a fluid delivery line andto an infusion container containing an infusion fluid, the infusionsystem comprising: a pump; at least one sensor connected to the pump orthe fluid delivery line, the at least one sensor configured to indicatewhether air is in the fluid delivery line; at least one processor inelectronic communication with the pump and the at least one sensor; anda memory in electronic communication with the at least one processor,wherein the memory comprises programming code for execution by the atleast one processor, and the programming code is configured to cause theat least one processor to determine an air determination related to theair in the fluid delivery line based on: (a) measurements taken by theat least one sensor, (b) medication information regarding the infusionfluid, and (c) infusion information regarding the infusion of theinfusion fluid.
 30. The infusion system of claim 29, wherein themedication information comprises a duration of the infusion fluid andthe infusion information comprises a volume of the infused fluid in theinfusion container.
 31. The infusion system of claim 29, wherein the airdetermination is further determined by statistical process controlcharts applied to the measurements taken by the at least one sensor. 32.The infusion system of claim 29, wherein the air determination comprisesdetermining an end-of-container event when the infusion container hasbeen emptied of the infusion fluid.
 33. An infusion system configured tobe connected to a fluid delivery line and to an infusion containercontaining an infusion fluid, the infusion system comprising: a pump; atleast one sensor connected to the pump or the fluid delivery line, theat least one sensor configured to indicate whether air is in the fluiddelivery line; at least one processor in electronic communication withthe pump and the at least one sensor; a memory in electroniccommunication with the at least one processor, the memory comprisingprogramming code for execution by the at least one processor; whereinthe programming code is configured to cause the at least one processorto determine an air determination related to the air in the fluiddelivery line based on: (a) infusion information regarding the infusionof the infusion fluid; and (b) statistical process control chartsapplied to multi-channel filtered measurements from the at least onesensor, wherein the multi-channel filtered measurements comprisemeasurements filtered by a plurality of Kalman filters.